Traya - Director - Data Science & Artificial Intelligence

Director - Data Science

Location: Mumbai or Bangalore

About Traya

Traya is a health-tech company that treats hair loss end-to-end through a personalized program combining dermatology, Ayurveda, nutrition, and behavioral science. We own the entire pathway - assessment, regimen design, coaching, refills, and protocol adjustments - powered by an adherence engine and outcomes data that improve results over time.

As Traya scales into an omnichannel health platform (web, app, clinics, tele-coaching), data science is the engine powering personalization, retention, and efficiency.

Why This Role Exists

This is a hands-on builder role for a leader who wants to take models from notebook to production. You will own Traya's machine learning roadmap end-to-end: building models that predict churn, optimize marketing spend, personalize regimens, and power recommendations - all tightly integrated with product and engineering.

The goal: ship ML systems that measurably improve LTV, retention, and funnel efficiency.

Your Mandate

1. Build High-Impact ML Models

- Design, train, and deploy models for churn prediction, lead scoring, regimen personalization, recommendations, and forecasting.

- Establish frameworks for uplift modeling, causal inference, and incrementality measurement.

- Continuously iterate and retrain models based on business feedback and new data.

2. Own MLOps & Model Lifecycle

- Partner with engineering to set up scalable pipelines (feature store, CI/CD for ML, monitoring).

- Build automated retraining and drift detection systems.

- Ensure models meet defined SLAs for latency, accuracy, and reliability in production.

3. Partner Closely with Product & Growth

- Translate business objectives into well-scoped ML problems.

- Collaborate with product managers to embed models into customer journeys and internal tools.

- Quantify and communicate model impact in terms of revenue, retention, and efficiency.

4. Build & Mentor a World-Class Team

- Hire, mentor, and upskill data scientists and ML engineers.

- Foster a culture of scientific rigor, experimentation, and measurable outcomes.





Key Outcomes to Deliver

Deployed ML Models: Productionize churn prediction, lead scoring, recommendation systems with measurable ROI.

Automation & Scalability: Fully operational MLOps pipelines with minimal manual intervention.

Business Impact: Demonstrable improvements in retention, funnel conversion, and payback period driven by ML systems.

Technical Excellence: Establish best practices for code quality, reproducibility, version control, and documentation.





Technical Toolkit

Languages & Libraries: Python (scikit-learn, XGBoost, PyTorch/TensorFlow, LightGBM).

Data & Pipelines: SQL, Airflow, Spark/Flink, Kafka/Kinesis, Snowflake/BigQuery.

MLOps: MLflow, Kubeflow, CI/CD tools, model monitoring frameworks.

Experimentation: A/B testing design, causal inference, uplift modeling.

Who You Are

years of experience in applied data science, ML engineering, or AI, with at least 2-3 years leading technical teams.

- Proven record of shipping production ML models that impacted growth or revenue.

- Deep expertise in supervised & unsupervised learning, recommendation systems, forecasting, and causal inference.

- Comfortable writing production-quality Python/SQL, reviewing code, and guiding ML architecture decisions.

- Experience in consumer-tech, D2C, health-tech, or marketplaces is a plus.

- Builder-operator mindset: thrives in ambiguous, high-growth environments, and loves to see models driving real business outcomes.

Traya provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, nation origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by central, state, or local laws.